1. Field of the Invention
This invention relates to prediction indicators, and particularly to systems and methods for distribution-transition estimation of key performance indicator (KPI).
2. Description of Background
Managing business performance by estimating KPIs or similar indices is known. For example, current business index processing systems find the appropriate capital structure for a certain capital outlay based on the probability distribution proportional to the profit from the money invested. Furthermore, business management systems, as scenarios, use a combination of databases that daily manage business index values and results from past simulations. Such systems assume an abundance of financial data and historical simulation results that can be directly used in calculations of estimated objectives. Other systems execute business simulations from the input of business indices or values that are the elements of business indices. Still other systems can, when required, calculate business indices based on the latest performance results and planning information. However, they do not include a viewpoint for finding distributions relation to business indices.
When considering the improvement of business performance via KPIs, changes over time as a distribution are viewed. However, in many systems, only single year data is available for KPIs during due diligence (hereafter DD) prior to concluding a contract, which makes direct future predictions difficult. This result leads to modelling using related data. However, the information gained from making predictions of future values via time-series analyses of historical data on indices that are strongly related to specified KPIs often results in point estimations. In addition, preparing detailed business scenarios for each point in the future allows visualization of the distribution information. However, the problems of estimating changes over time in the scenarios occurs. Hence, the problem repeats itself. Further, preparing business scenarios for each point increases the distribution combinations giving rise to increased calculation time. Therefore, there is a need for systems and methods for estimating changes in KPI distributions that take in account the equivalent of transitions in scenario changes.